The area that intrigued me the most was in enhancing customer experiences. Mathers elaborates, "We've seen consumer companies like L'Oreal, Whole Foods, and a membership club in the wine and spirits space, innovating how they can simplify, improve and remove barriers to purchase. L'Oreal has built tools into their mobile app so you can apply cosmetics while standing in a drug store and see whether it's the right shade for you. Whole Foods is using some of their tools with their recipes site so you can pop in a couple of ingredients that you have and it starts pushing you a couple more things that you might want to buy in the store. So, growing basket size or helping people expand their grocery list if they're meal planning. And then this winemaker has talked a lot about how millennials tend to experiment. They try lots of new wines, they enjoy the process of trying those wines, but they don't know a ton about the category as a whole. And so the winemaker is using conversational commerce and experimenting with chatbots to recommend the right wine for them based on a couple of easy questions So, I think a lot of cool opportunities to use AI to ease the buying process on the consumer side."

The pace of progress is ramping up so quickly in this space, it's useful to pause for a refresher on what AI and machine learning actually are. Artificial intelligence is the study of how to make machines intelligent or capable of solving problems as well as people can. At its core, machine learning is a new way of creating those problem-solving systems. For decades, programmers manually coded computer programs to provide outputs when given a certain input. With machine learning, we teach computers to learn without having to program them with a rigid set of rules.

This guest post was contributed by Steve Sirich, Head of Marketing at Bing Ads, Microsoft. There's no doubt that technology is reshaping the way that brands engage with consumers. Artificial intelligence (AI) and machine learning technologies, such as Microsoft's Cortana and Amazon's Alexa, are advancing rapidly and have become increasingly ubiquitous in our daily lives, transforming how we interact with the world around us. As consumers we tend to embrace these technologies because they satisfy our desire for convenience and personalization. As AI and machine learning become more capable and more embedded in our digital experiences, brands will also have to rethink how they engage with consumers.

Artificial intelligence and machine learning are starting to have a real impact on marketing, and the executives we've spoken to can't wait for more. The topic has come up on many episodes of "The Marketing Garage" -- our podcast that talks to marketing executives about their technology -- as the tech marketers are most excited for in the future. This month we interviewed Adelyn Zhou, head of marketing for TopBots, a strategy and research firm in applied AI. "A lot of lead scoring is going to be improved significantly with AI," says Zhou. "If you actually use real AI, there's a significant enhancement in terms of personalization, understanding who's going to buy, who's not, and creating similar target market segments that can lead to significant lifts." As an example, she points to Harley Davidson, which increased sales leads over 2000 percent by using a system that scored leads "in a much more intelligent way." The one area many people thought AI could not help is turning out to be one of the most fertile: Creative.

Google announced that it is officially killing last-click attribution at Marketing Next 2017, the companies annual event to promote ad products, analytics, and Double Click. Google launched Google Attribution, the companies new product which uses machine learning to assign a weighted value to every different touch point along the consumer's path to purchase. Last-click model used by digital marketers gives the last-click credit for sale or conversion. With the convergence of offline and online channels, the model was always debated to be not suitable when it comes to evaluating media effectiveness. With this new attribution model, the goal is to bring in more efficiency when it comes to media spends across channels and devices.

Voice is a fast-growing channel, which aligns with consumer expectations for more instant task delivery and more integrated connectivity with devices, apps and channels. The opportunity for marketers is exciting and the scope for brand engagement with customers is huge. Crucially, AI assistants have the potential become new sources of data capture and rich hubs for behavior-based customer insights.

With the ability to make intelligent decisions based on data and behavior triggers, Oracle states that it will help users streamline business tasks and provide them with individualized recommendations for engaging with prospective customers. The announcement, named Adaptive Intelligent Applications, was made at the company's annual OpenWorld Conference and came shortly after Salesforce unveiled its Einstein project, which will incorporate AI into its core cloud offerings. The moves may also be connected to buyer needs. In a study conducted by Marketing ID (a sister publication to Demand Gen Report), one-third (33%) of marketers surveyed say their top budget priority will be predictive tools, slightly more than CRM integration (31%) and campaign reporting and metrics (31%). Industry experts noted that AI will provide users with insights into customer activities they haven't had access to previously.